{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T06:40:10Z","timestamp":1751697610784,"version":"3.41.0"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319930367"},{"type":"electronic","value":"9783319930374"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-93037-4_22","type":"book-chapter","created":{"date-parts":[[2018,6,19]],"date-time":"2018-06-19T16:00:13Z","timestamp":1529424013000},"page":"275-287","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Category Multi-representation: A Unified Solution for Named Entity Recognition in Clinical Texts"],"prefix":"10.1007","author":[{"given":"Jiangtao","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Juanzi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Shuai","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yixin","family":"Cao","sequence":"additional","affiliation":[]},{"given":"Lei","family":"Hou","sequence":"additional","affiliation":[]},{"given":"Xiao-Li","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,6,20]]},"reference":[{"key":"22_CR1","unstructured":"Abacha, A.B., Zweigenbaum, P.: Medical entity recognition: a comparison of semantic and statistical methods. In: BioNLP, pp. 56\u201364 (2011)"},{"key":"22_CR2","first-page":"229","volume":"17","author":"AR Aronson","year":"2010","unstructured":"Aronson, A.R., Lang, F.M.: An overview of metamap: historical perspective and recent advances. JAMIA 17, 229\u2013236 (2010)","journal-title":"JAMIA"},{"issue":"90001","key":"22_CR3","doi-asserted-by":"publisher","first-page":"267D","DOI":"10.1093\/nar\/gkh061","volume":"32","author":"O. Bodenreider","year":"2004","unstructured":"Bodenreider, O.: The unified medical language system (UMLS): integrating biomedical terminology (2004)","journal-title":"Nucleic Acids Research"},{"key":"22_CR4","unstructured":"Bodnari, A., Del\u00e9ger, L., Lavergne, T., N\u00e9v\u00e9ol, A., Zweigenbaum, P.: A supervised named-entity extraction system for medical text. In: Working Notes for CLEF Conference (2013)"},{"key":"22_CR5","unstructured":"Bodnari, A., Del\u00e9ger, L., Lavergne, T., N\u00e9v\u00e9ol, A., Zweigenbaum, P.: A supervised named-entity extraction system for medical text. In: CLEF (2013)"},{"issue":"5","key":"22_CR6","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1136\/amiajnl-2011-000150","volume":"18","author":"B de Bruijn","year":"2011","unstructured":"de Bruijn, B., Cherry, C., Kiritchenko, S., Martin, J., Zhu, X.: Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010. J. Am. Med. Inform. Assoc. 18(5), 557 (2011)","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"22_CR7","doi-asserted-by":"crossref","unstructured":"Chapman, W.W., Chu, D., Dowling, J.N.: Context: an algorithm for identifying contextual features from clinical text. In: BioNLP 2007, pp. 81\u201388 (2007)","DOI":"10.3115\/1572392.1572408"},{"issue":"3","key":"22_CR8","first-page":"596","volume":"24","author":"F Dernoncourt","year":"2017","unstructured":"Dernoncourt, F., Lee, J.Y., Uzuner, \u00d6., Szolovits, P.: De-identification of patient notes with recurrent neural networks. JAMIA 24(3), 596\u2013606 (2017)","journal-title":"JAMIA"},{"key":"22_CR9","first-page":"279","volume":"121","author":"K Donnelly","year":"2006","unstructured":"Donnelly, K.: SNOMED-CT: the advanced terminology and coding system for eHealth. Stud. Health Technol. Inform. 121, 279\u201390 (2006)","journal-title":"Stud. Health Technol. Inform."},{"key":"22_CR10","first-page":"601","volume":"18","author":"M Jiang","year":"2011","unstructured":"Jiang, M., Chen, Y., Liu, M., Rosenbloom, S.T., Mani, S., Denny, J.C., Xu, H.: A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries. JAMIA 18, 601\u2013606 (2011)","journal-title":"JAMIA"},{"key":"22_CR11","doi-asserted-by":"publisher","first-page":"160035","DOI":"10.1038\/sdata.2016.35","volume":"3","author":"AEW Johnson","year":"2016","unstructured":"Johnson, A.E.W., Pollard, T.J., Shen, L., Lehman, L.H., Feng, M., Ghassemi, M., Moody, B., Szolovits, P., Celi, L.A., Mark, R.G.: MIMIC-III, a freely accessible critical care database. Sci. Data 3, 160035 (2016)","journal-title":"Sci. Data"},{"key":"22_CR12","doi-asserted-by":"crossref","unstructured":"Kundeti, S.R., Vijayananda, J., Mujjiga, S., Kalyan, M.: Clinical named entity recognition: challenges and opportunities. In: 2016 IEEE International Conference on Big Data, pp. 1937\u20131945 (2016)","DOI":"10.1109\/BigData.2016.7840814"},{"key":"22_CR13","doi-asserted-by":"crossref","unstructured":"Li, L., Jin, L., Jiang, Z., Song, D., Huang, D.: Biomedical named entity recognition based on extended recurrent neural networks. In: BIBM, pp. 649\u2013652 (2015)","DOI":"10.1109\/BIBM.2015.7359761"},{"issue":"4","key":"22_CR14","doi-asserted-by":"publisher","first-page":"848","DOI":"10.3390\/info6040848","volume":"6","author":"S Liu","year":"2015","unstructured":"Liu, S., Tang, B., Chen, Q., Wang, X.: Effects of semantic features on machine learning-based drug name recognition systems: word embeddings vs. manually constructed dictionaries. Information 6(4), 848\u2013865 (2015)","journal-title":"Information"},{"key":"22_CR15","first-page":"128","volume":"35","author":"SM Meystre","year":"2008","unstructured":"Meystre, S.M., Savova, G.K., Kipper-Schuler, K.C., Hurdle, J.F.: Extracting information from textual documents in the electronic health record: a review of recent research. Yearb. Med. Inform. 35, 128\u2013144 (2008)","journal-title":"Yearb. Med. Inform."},{"key":"22_CR16","first-page":"3111","volume":"26","author":"T Mikolov","year":"2013","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. Adv. Neural Inf. Proc. Syst. 26, 3111\u20133119 (2013)","journal-title":"Adv. Neural Inf. Proc. Syst."},{"key":"22_CR17","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.D.: Glove: global vectors for word representation. In: EMNLP, vol. 14, pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"22_CR18","doi-asserted-by":"crossref","unstructured":"Ratinov, L., Roth, D.: Design challenges and misconceptions in named entity recognition. In: CoNLL (2009)","DOI":"10.3115\/1596374.1596399"},{"key":"22_CR19","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1155\/2016\/3483528","volume":"2016","author":"M Sadikin","year":"2016","unstructured":"Sadikin, M., Fanany, M.I., Basaruddin, T.: A new data representation based on training data characteristics to extract drug name entity in medical text. Comput. Intell. Neurosci. 2016, 16 (2016)","journal-title":"Comput. Intell. Neurosci."},{"issue":"5","key":"22_CR20","first-page":"507","volume":"17","author":"GK Savova","year":"2010","unstructured":"Savova, G.K., Masanz, J.J., Ogren, P.V., Zheng, J., Sohn, S., Kipper-Schuler, K.C., Chute, C.G.: Mayo clinical text analysis and knowledge extraction system (cTAKES): architecture, component evaluation and applications. JAMIA 17(5), 507\u2013513 (2010)","journal-title":"JAMIA"},{"key":"22_CR21","doi-asserted-by":"crossref","unstructured":"Settles, B.: Biomedical named entity recognition using conditional random fields and rich feature sets. In: JNLPBA, pp. 104\u2013107 (2004)","DOI":"10.3115\/1567594.1567618"},{"key":"22_CR22","doi-asserted-by":"crossref","unstructured":"Shen, D., Zhang, J., Zhou, G., Su, J., Tan, C.L.: Effective adaptation of a hidden Markov model-based named entity recognizer for biomedical domain. In: BioMed, pp. 49\u201356 (2003)","DOI":"10.3115\/1118958.1118965"},{"key":"22_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"212","DOI":"10.1007\/978-3-642-40802-1_24","volume-title":"Information Access Evaluation. Multilinguality, Multimodality, and Visualization","author":"H Suominen","year":"2013","unstructured":"Suominen, H., Salanter\u00e4, S., Velupillai, S., Chapman, W.W., Savova, G., Elhadad, N., Pradhan, S., South, B.R., Mowery, D.L., Jones, G.J.F., Leveling, J., Kelly, L., Goeuriot, L., Martinez, D., Zuccon, G.: Overview of the ShARe\/CLEF eHealth evaluation lab 2013. In: Forner, P., M\u00fcller, H., Paredes, R., Rosso, P., Stein, B. (eds.) CLEF 2013. LNCS, vol. 8138, pp. 212\u2013231. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-40802-1_24"},{"key":"22_CR24","doi-asserted-by":"crossref","unstructured":"Takeuchi, K., Collier, N.: Bio-medical entity extraction using support vector machines. In: BioMed, pp. 57\u201364 (2003)","DOI":"10.3115\/1118958.1118966"},{"issue":"5","key":"22_CR25","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1136\/amiajnl-2011-000203","volume":"18","author":"\u00d6 Uzuner","year":"2011","unstructured":"Uzuner, \u00d6., South, B.R., Shen, S., DuVall, S.L.: 2010 i2b2\/VA challenge on concepts, assertions, and relations in clinical text. J. Am. Med. Inform. Assoc. 18(5), 552 (2011)","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"22_CR26","doi-asserted-by":"publisher","first-page":"baw140","DOI":"10.1093\/database\/baw140","volume":"2016","author":"Qikang Wei","year":"2016","unstructured":"Wei, Q., Chen, T., Xu, R., He, Y., Gui, L.: Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks. In: Database 2016 (2016)","journal-title":"Database"},{"key":"22_CR27","first-page":"1","volume":"9","author":"Y Xu","year":"2014","unstructured":"Xu, Y., Hua, J., Ni, Z., Chen, Q., Fan, Y., Ananiadou, S., Chang, E.I.C., Tsujii, J.: Anatomical entity recognition with a hierarchical framework augmented by external resources. Plos One 9, 1\u201313 (2014)","journal-title":"Plos One"},{"key":"22_CR28","doi-asserted-by":"crossref","unstructured":"Zeng, D., Sun, C., Lin, L., Liu, B.: Enlarging drug dictionary with semi-supervised learning for drug entity recognition. In: BIBM, pp. 1929\u20131931 (2016)","DOI":"10.1109\/BIBM.2016.7822818"},{"key":"22_CR29","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Yang, Z., Luo, L., Zhang, Y., Wang, L., Lin, H., Wang, J.: ML-CNN: a novel deep learning based disease named entity recognition architecture. In: BIBM, p. 794 (2016)","DOI":"10.1109\/BIBM.2016.7822625"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-93037-4_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,5]],"date-time":"2025-07-05T06:13:08Z","timestamp":1751695988000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-93037-4_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319930367","9783319930374"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-93037-4_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"20 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Melbourne, VIC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 June 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 June 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/prada-research.net\/pakdd18\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}